Volume 4, Issue 4 (Autumn 2015)                   JOHE 2015, 4(4): 229-240 | Back to browse issues page



DOI: 10.18869/acadpub.johe.4.4.229
PMCID: 0

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Safaei A, Azad M, Abdi F. A suitable data model for HIV infection and epidemic detection. JOHE. 2015; 4 (4) :229-240
URL: http://johe.rums.ac.ir/article-1-167-en.html

Assistant Prof., Dept. of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran , aa.safaei@modares.ac.ir
Abstract:   (404 Views)

Background: In recent years, there has been an increase in the amount and variety of data generated in the field of healthcare, (e.g., data related to the prevalence of contagious diseases in the society). Various patterns of individuals’ relationships in the society make the analysis of the network a complex, highly important process in detecting and preventing the incidence of diseases. Therefore, it would be helpful to propose a model for storing and processing related data which is especially designed for such an application.

Materials and Methods: In this paper, a data model is proposed for the management of data for individuals infected with contagious diseases. This data model has the ability to efficiently detect the path of infectious diseases and the probable epidemicity. The proposed model is based on the graph data model, a type of NoSQL data model. In order to design this data model, essential requirements and queries were determined based on the needs of experts in this field.

Results: The proposed data model was experimentally evaluated using Neo4j, a well-known graph data management system. It is shown in this paper that the proposed data model has a better performance than the traditional relational model in terms of system utilization and performance (i.e., data storage space, complexity and the time of finding the shortest infection path between two individuals, traversing the graph, finding at risk individuals, and etc.).

Conclusions: The management of data for epidemic detection of HIV infection requires an appropriate data model that can provide the required functionalities and features with an acceptable quality. Graph data models are suitable NoSQL models for some of these features (e.g., epidemic detection via traversing of the graph). The proposed graph-based data model provides the main functionalities and features while outperforming performance and utilization metrics.

Keywords: Model [MeSH], Contagious [MeSH], Disease [MeSH], Epidemic [MeSH], HIV [MeSH],
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Type of Study: original article | Subject: Epidemiology

References
1. Hatemi H, Razavi SM, Eftekhar H. Comprehensive volume of Public Health. 2nd ed. Tehran: Arjomand Publication; 2012. Chapter 8, Part 12, Investigation and Control of Epidemics; P.1010-22.
2. Hey T, Tansley S, Tolle K. The Fourth Paradigm: Data-Intensive Scientific Discovery. 1st ed. New York, United States of America: Microsoft Research; 2009. P.91-134.
3. Stattner E, Vidot N. Social network analysis in epidemiology: Current trends and perspectives. Paper presented at: The 5th International Conference on Research Challenges in Information Science (RCIS), 2011 May 19-21; Gosier, Guadeloupe.
4. Salathe M, Jones JH. Dynamics and control of diseases in networks with community structure. PLoS Comput Biol 2010; 6(4):1-11.
5. Han J, Haihong E, Le G, Du J. Survey on NoSQL database. Paper presented at: The 6th International Conference on Pervasive Computing and Applications (ICPCA); 2011 Oct 26-28; Port Elizabeth, South Africa.
6. Leavitt N. Will NoSQL databases live up to their promise? Computer 2010; 43(2):12-4.
7. Strauch Ch. NoSQL databases. Lecture Selected Topics on Software-Technology Ultra-Large Scale Sites, Stuttgart Media University. 2011. 149 p. Available from: www.christof-strauch.de/nosqldbs.pdf
8. Powers KA, Ghani AC, Miller WC, Hoffman IF, Pettifor AE, Kamanga G, et al. The role of acute and early HIV infection in the spread of HIV and implications for transmission prevention strategies in Lilongwe, Malawi: a modelling study. Lancet 2011; 378(9787):256-68.
9. Miller WC, Rosenberg NE, Rutstein SE, Powers KA. The role of acute and early HIV infection in the sexual transmission of HIV. Curr Opin HIV AIDS 2010; 5(4):277-82.
10. Basavaraj KH, Navya MA, Rashmi R. Quality of life in HIV/AIDS. Indian J Sex Transm Dis 2010; 31(2):75-80.
11. Levinson W, Jawetz E. Medical microbiology and immunology: examination & board review. 8th ed. New York, N.Y.: Lange Medical Books/Mc Graw -Hill; 2004.
12. EI-Sappagh ShH, El-Masri S; Riad AM; Elmogy M. Electronic health record data model optimized for knowledge discovery. International Journal of Computer Science Issues 2012; 9(5):329.

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